Data Connectors (LlamaHub)#
Concept#
A data connector (aka Reader
) ingest data from different data sources and data formats into a simple Document
representation (text and simple metadata).
Tip
Once you’ve ingested your data, you can build an Index on top, ask questions using a Query Engine, and have a conversation using a Chat Engine.
LlamaHub#
Our data connectors are offered through LlamaHub 🦙. LlamaHub is an open-source repository containing data loaders that you can easily plug and play into any LlamaIndex application.
Usage Pattern#
Get started with:
from llama_index.core import download_loader
from llama_index.readers.google import GoogleDocsReader
loader = GoogleDocsReader()
documents = loader.load_data(document_ids=[...])
Modules#
Some sample data connectors:
local file directory (
SimpleDirectoryReader
). Can support parsing a wide range of file types:.pdf
,.jpg
,.png
,.docx
, etc.Notion (
NotionPageReader
)Google Docs (
GoogleDocsReader
)Slack (
SlackReader
)Discord (
DiscordReader
)Apify Actors (
ApifyActor
). Can crawl the web, scrape webpages, extract text content, download files including.pdf
,.jpg
,.png
,.docx
, etc.
See below for detailed guides.
- Module Guides
- Simple Directory Reader
- Psychic Reader
- DeepLake Reader
- Qdrant Reader
- Discord Reader
- MongoDB Reader
- Chroma Reader
- MyScale Reader
- Faiss Reader
- Obsidian Reader
- Slack Reader
- Web Page Reader
- Pinecone Reader
- Pathway Reader
- Mbox Reader
- MilvusReader
- Notion Reader
- Github Repo Reader
- Google Docs Reader
- Database Reader
- Twitter Reader
- Weaviate Reader
- Make Reader
- Deplot Reader Demo